Network-based strategies in metabolomics data analysis and interpretation: from molecular networking to biological interpretation

Leonardo Perez De Souza, Saleh Alseekh, Yariv Brotman, Alisdair R. Fernie

Research output: Contribution to journalReview articlepeer-review

21 Scopus citations

Abstract

Introduction: Metabolomics has become a crucial part of systems biology; however, data analysis is still often undertaken in a reductionist way focusing on changes in individual metabolites. Whilst such approaches indeed provide relevant insights into the metabolic phenotype of an organism, the intricate nature of metabolic relationships may be better explored when considering the whole system. Areas covered: This review highlights multiple network strategies that can be applied for metabolomics data analysis from different perspectives including: association networks based on quantitative information, mass spectra similarity networks to assist metabolite annotation and biochemical networks for systematic data interpretation. We also highlight some relevant insights into metabolic organization obtained through the exploration of such approaches. Expert opinion: Network based analysis is an established method that allows the identification of non-intuitive metabolic relationships as well as the identification of unknown compounds in mass spectrometry. Additionally, the representation of data from metabolomics within the context of metabolic networks is intuitive and allows for the use of statistical analysis that can better summarize relevant metabolic changes from a systematic perspective.

Original languageEnglish
Pages (from-to)243-255
Number of pages13
JournalExpert Review of Proteomics
Volume17
Issue number4
DOIs
StatePublished - 2 Apr 2020

Keywords

  • Metabolomics
  • correlation
  • network

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